Find More Like This: Prospecting From Winners
Pick 1-5 of your best customers. InsightSignal builds the ICP, fetches matching candidates, and verifies them — closing the prospecting loop.
From "we want more like them" to a verified list
Every sales leader has had this conversation. A few accounts close beautifully, the team learns what "good" actually looks like, and the question at the next pipeline review is inevitable — how do we find more like these? The standard answer is a three-week project: someone writes a fresh ICP brief, RevOps queries a database, marketing builds a campaign, and a mixed-quality list eventually lands in the CRM. By then, the timing window that made the original signal interesting has closed. Find More Like This collapses that loop. You pick the accounts that already worked out and InsightSignal builds the next list from the pattern they share — synthesized, fetched, and verified.
When Find More Like This is the right tool
Find More Like This is purpose-built for prospect pool expansion from known winners. Reach for it when:
- You have a small list of accounts that have already worked out. Closed deals, validated partners, ideal investments — anywhere you can point to companies and say "we want more of these."
- You're scouting expansion, partnerships, or investment targets. Any motion where the literal question is "more like these."
- You want a fresh pool synthesized from a real pattern. Not a hand-written brief that interprets what you said.
If you already have a list to verify, CSV Upload is the right tool. If you want a deep dive on one account, Research Reports do that. Find More Like This is for expansion, not validation or single-account intelligence.
Picking seeds that produce a clean pool
Seeds drive everything downstream. The system mirrors the pattern your seeds share, so a few guidelines pay off:
- Pick proven wins, not hopefuls. Seed with companies that already closed, retained, or expanded — not the ones you wish would. The pool reflects the pattern you feed in.
- Fewer is better. One strong seed produces a tight, focused pool. Five seeds spanning different industries dilute the pattern and produce a noisier list.
- Match seeds to the question. Want "more dermatology clinics like Acme"? Seed with dermatology clinics — not a clinic plus a healthtech SaaS vendor. The pattern should be coherent.
The wizard caps you at 5 seeds. Quality of pattern beats quantity of examples.
What happens when you click Find More Like This
From the Companies page, select your seeds and click Find More Like This. The wizard runs through four steps shown as a progress strip at the top:
- Synthesize. InsightSignal reads the seeds' industry, size, location, revenue, and any intent signals, then builds an editable Ideal Customer Profile. About 5-15 seconds. No credit cost.
- Refine. Adjust filters — industry, geography, employee range, revenue band — and watch candidate counts update live. Three strategy presets control how aggressively candidates are cross-validated.
- Preview (optional). Pay a small flat fee to see real sample candidates from the data network before committing to a full run.
- Launch. Confirm pool size and the credit estimate. The run starts in the background and you navigate to a live progress page.
Synthesize and Refine are free. The first credit charge only happens when you opt into a sample preview or click Launch.
Choosing a strategy preset
The strategy preset controls how InsightSignal blends data sources when fetching candidates:
| Preset | Best for |
|---|---|
| Balanced (default) | Most runs. Mix of coverage and cost. |
| Cost-focused | Bulk discovery where you'll prune downstream. |
| Coverage-focused | Maximum cross-validation. Higher confidence, higher cost. |
Geographic ICPs (with State or City filters) automatically route through the source best suited for sub-national filtering, regardless of the preset you pick.
After Launch: fetch, review, verify
Once you confirm, the run moves through three phases — with a chance to course-correct between phases two and three.
- Fetch and dedupe. InsightSignal pulls candidates matching your filters, removes any already in your database, deduplicates against the seeds, and ranks the rest. Typically 30 seconds to a few minutes.
- Candidate review. The run pauses on a selection screen showing every fetched candidate with industry, size, location, ranking score, and which sources found it. Deselect anything that doesn't fit — the credit hold trims to match what you keep.
- Verification. Each kept candidate runs through the same multi-source verification as a CSV upload. Verified companies appear in your Companies list as each one finishes — not at the end of the batch.
What it costs
Find More Like This bills credits at three points across a run. You can stop at any of them.
| Stage | Cost |
|---|---|
| Synthesize and Refine | Free |
| Sample preview (optional) | Small flat fee per click |
| Fetch | ~1 credit per candidate kept in the pool |
| Verification | Standard per-row rate, same as CSV uploads |
Launch places a hold for the worst-case run. As stages complete, the hold settles to actual cost and the unused portion returns to your balance. Cancel at any stage and you only pay for what's already settled.
If you walk away before finalizing
If fetch completes and you don't finalize your selection, InsightSignal holds the verification credits for 48 hours and then automatically abandons the run. The hold returns to your balance, you'll see a notification with the credit amount, and the fetched candidates remain in your database as Discovered Entities. They just won't be auto-verified. To pick them up later, start a fresh run.
What you build with every run
Every Find More Like This run produces two things you can keep building on:
- A new cohort of verified A and B candidates. Ranked, scored, ready to outreach — landed directly in your Companies list as they finish.
- A synthesized Ideal Customer Profile. Automatically saved to your Intents library. Editable, reusable on other CSV uploads, or applicable as a lens on existing data.
And the winners from this run become the strongest possible seeds for the next one. That's the closed loop the feature is built around — and the practical answer to the broader question in The Prospecting Data Problem Nobody Talks About.
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